Academic literature on the topic 'GB-InSAR'

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Journal articles on the topic "GB-InSAR"

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Xiao, Ting, Wei Huang, Yunkai Deng, Weiming Tian, and Yonglian Sha. "Long-Term and Emergency Monitoring of Zhongbao Landslide Using Space-Borne and Ground-Based InSAR." Remote Sensing 13, no. 8 (April 19, 2021): 1578. http://dx.doi.org/10.3390/rs13081578.

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This work presents the ideal combination of space-borne and ground-based (GB) Interferometric Synthetic Aperture Radar (InSAR) applications. In the absence of early investigation reporting and specialized monitoring, the Zhongbao landslide unexpectedly occurred on 25 July 2020, forming a barrier lake that caused an emergency. As an emergency measure, the GB-InSAR system was installed 1.8 km opposite the landslide to assess real-time cumulative deformation with a monitoring frequency of 3 min. A zone of strong deformation was detected, with 178 mm deformation accumulated within 15 h, and then a successful emergency warning was issued to evacuate on-site personnel. Post-event InSAR analysis of 19 images acquired by the ESA Sentinel-1 from December 2019 to August 2020 revealed that the landslide started in March 2020. However, the deformation time series obtained from satellite InSAR did not show any signs that the landslide had occurred. The results suggest that satellite InSAR is effective for mapping unstable areas but is not qualified for rapid landslide monitoring and timely warning. The GB-InSAR system performs well in monitoring and providing early warning, even with dense vegetation on the landslide. The results show the shortcomings of satellite InSAR and GB-InSAR and a clearer understanding of the necessity of combining multiple monitoring methods.
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Ferrigno, Federica, Giovanni Gigli, Riccardo Fanti, Emanuele Intrieri, and Nicola Casagli. "GB-InSAR monitoring and observational method for landslide emergency management: the Montaguto earthflow (AV, Italy)." Natural Hazards and Earth System Sciences 17, no. 6 (June 9, 2017): 845–60. http://dx.doi.org/10.5194/nhess-17-845-2017.

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Abstract. On 10 March 2010, because of the heavy rainfall in the preceding days, the Montaguto landslide (Southern Italy) reactivated, affecting both state road 90 Delle Puglie and the Rome–Bari railway. A similar event occurred on May 2005 and on September 2009. As a result, the National Civil Protection Department (DPC) started an accurate monitoring and analysis program. A monitoring project using the GB-InSAR (ground-based interferometric synthetic aperture radar) system was emplaced to investigate the landslide kinematics, plan urgent safety measures for risk mitigation and design long-term stabilization work.Here, we present the GB-InSAR monitoring system results and its applications in the observational method (OM) approach. GB-InSAR is an established instrument for long-term campaigns aimed at early warning and monitoring during construction works. Our paper further develops these aspects in that it highlights how the OM based on the GB-InSAR technique can produce savings in terms of cost and time in engineering projects without compromising safety. This study focuses on the key role played by the monitoring activities during the design and planning activities, with special reference to the emergency phase.
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Wang, Peng, Cheng Xing, and Xiandong Pan. "Reservoir Dam Surface Deformation Monitoring by Differential GB-InSAR Based on Image Subsets." Sensors 20, no. 2 (January 10, 2020): 396. http://dx.doi.org/10.3390/s20020396.

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Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.
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Zheng, Xiangtian, Xiufeng He, Xiaolin Yang, Haitao Ma, Zhengxing Yu, Guiwen Ren, Jiang Li, Hao Zhang, and Jinsong Zhang. "Terrain Point Cloud Assisted GB-InSAR Slope and Pavement Deformation Differentiate Method in an Open-Pit Mine." Sensors 20, no. 8 (April 20, 2020): 2337. http://dx.doi.org/10.3390/s20082337.

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Ground-based synthetic aperture radar interferometry (GB-InSAR) is a valuable tool for deformation monitoring. The 2D interferograms obtained by GB-InSAR can be integrated with a 3D terrain model to visually and accurately locate deformed areas. The process has been preliminarily realized by geometric mapping assisted by terrestrial laser scanning (TLS). However, due to the line-of-sight (LOS) deformation monitoring, shadow and layover often occur in topographically rugged areas, which makes it difficult to distinguish the deformed points on the slope between the ones on the pavement. The extant resampling and interpolation method, which is designed for solving the scale difference between the point cloud and radar pixels, does not consider the local scattering characteristics difference of slope. The scattering difference information of road surface and slope surface in the terrain model is deeply weakened. We propose a differentiated method with integrated GB-InSAR and terrain surface point cloud. Local geometric and scattering characteristics of the slope were extracted, which account for pavement and slope differentiating. The geometric model is based on a GB-InSAR system with linear repeated-pass and the topographic point cloud relative observation geometry. The scattering model is based on k-nearest neighbor (KNN) points in small patches varies as radar micro-wave incident angle changes. Simulation and a field experiment were conducted in an open-pit mine. The results show that the proposed method effectively distinguishes pavement and slope surface deformation and the abnormal area boundary is partially relieved.
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Han, Jianfeng, Honglei Yang, Youfeng Liu, Zhaowei Lu, Kai Zeng, and Runcheng Jiao. "A Deep Learning Application for Deformation Prediction from Ground-Based InSAR." Remote Sensing 14, no. 20 (October 11, 2022): 5067. http://dx.doi.org/10.3390/rs14205067.

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Ground-based synthetic aperture radar interferometry (GB-InSAR) has the characteristics of high precision, high temporal resolution, and high spatial resolution, and is widely used in highwall deformation monitoring. The traditional GB-InSAR real-time processing method is to process the whole data set or group in time sequence. This type of method takes up a lot of computer memory, has low efficiency, cannot meet the timeliness of slope monitoring, and cannot perform deformation prediction and disaster warning forecasting. In response to this problem, this paper proposes a GB-InSAR time series processing method based on the LSTM (long short-term memory) model. First, according to the early monitoring data of GBSAR equipment, the time series InSAR method (PS-InSAR, SBAS, etc.) is used to obtain the initial deformation information. According to the deformation calculated in the previous stage and the atmospheric environmental parameters monitored, the LSTM model is used to predict the deformation and atmospheric delay at the next time. The phase is removed from the interference phase, and finally the residual phase is unwrapped using the spatial domain unwrapping algorithm to solve the residual deformation. The predicted deformation and the residual deformation are added to obtain the deformation amount at the current moment. This method only needs to process the difference map at the current moment, which greatly saves time series processing time and can realize the prediction of deformation variables. The reliability of the proposed method is verified by ground-based SAR monitoring data of the Guangyuan landslide in Sichuan Province.
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Ferrigno, F., G. Gigli, R. Fanti, and N. Casagli. "GB-InSAR monitoring and observational method for landslide emergency management: the Montaguto earthflow (AV, Italy)." Natural Hazards and Earth System Sciences Discussions 3, no. 12 (December 7, 2015): 7247–73. http://dx.doi.org/10.5194/nhessd-3-7247-2015.

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Abstract. On 10 March 2010, due to the heavy rainfall that occurred on the previous days, the Montaguto earthflow reactivated, involving the road SS 90 "Delle Puglie", as had happened previously in May 2005 and in September 2009, and reaching the Roma–Bari railway. This determined a special attention of the National Civil Protection Department and a widespread monitoring and analysis program was initiated. A monitoring activity using GB-InSAR (Ground Based Interferometric Synthetic Aperture Radar) system began, in order to investigate the landslide kinematics, to plan urgent safety measures for risk mitigation and to design long term stabilization work. In this paper the GB-InSAR monitoring system results and its applications in the Observational Method (OM) approach are presented. The paper also highlights how the OM based on the GB-InSAR technique can produce savings in cost and time on engineering projects, without compromising safety, and how it can also benefit the geotechnical community by increasing scientific knowledge. This study focuses on the very much active role played by the monitoring activities, in both the design and plan modifications; with a special consideration for the emergency phase.
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Qiu, Zhiwei, Minglian Jiao, Tinchen Jiang, and Li Zhou. "Dam Structure Deformation Monitoring by GB-InSAR Approach." IEEE Access 8 (2020): 123287–96. http://dx.doi.org/10.1109/access.2020.3005343.

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Lin, Zihao, Yan Duan, Yunkai Deng, Weiming Tian, and Zheng Zhao. "An Improved Multi-Baseline Phase Unwrapping Method for GB-InSAR." Remote Sensing 14, no. 11 (May 26, 2022): 2543. http://dx.doi.org/10.3390/rs14112543.

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Ground-based interferometric synthetic aperture radar (GB-InSAR) technology can be applied to generate a digital elevation model (DEM) with high spatial resolution and high accuracy. Phase unwrapping is a critical procedure, and unwrapping errors cannot be effectively avoided in the interferometric measurements of terrains with discontinuous heights. In this paper, an improved multi-baseline phase unwrapping (MB PU) method for GB-InSAR is proposed. This method combines the advantages of the cluster-analysis-based MB PU algorithm and the minimum cost flow (MCF) method. A cluster-analysis-based MB PU algorithm (CA-based MB PU) is firstly utilized to unwrap the clustered pixels with high phase quality. Under the topological constraints of a triangulation network, the connectivity graph of any non-clustered pixel is established with its adjacent unwrapped cluster pixels. Then, the absolute phase of these non-clustered pixels can be identified using the MCF method. Additionally, a spatial-distribution-based denoising algorithm is utilized to denoise the data in order to further improve the accuracy of the phase unwrapping. The DEM generated by one GB-InSAR is compared with that generated by light detection and ranging (LiDAR). Both simulated and experimental datasets are utilized to verify the effectiveness and robustness of this improved method.
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Del Ventisette, C., E. Intrieri, G. Luzi, N. Casagli, R. Fanti, and D. Leva. "Using ground based radar interferometry during emergency: the case of the A3 motorway (Calabria Region, Italy) threatened by a landslide." Natural Hazards and Earth System Sciences 11, no. 9 (September 22, 2011): 2483–95. http://dx.doi.org/10.5194/nhess-11-2483-2011.

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Abstract. The rapid assessment of the evolution of the phenomena which occur during an emergency, along with an all weather and h24 monitoring capability, are probably the main characteristics of a system aimed at optimizing intervention in natural disasters, such as landslide collapses. A few techniques are able to provide all these features remotely, hence assuring safe conditions to operators. This paper reports on an application of the GB-InSAR (Ground-Based Interferometric Synthetic Aperture Radar) technique to monitor a landslide threatening an infrastructure, the A3 motorway in the Calabria Region (Southern Italy), in emergency conditions. Here, it is evaluated how well this technique is able to satisfy these requirements. On 30 January 2009, a mass movement never detected before and located near Santa Trada viaduct caused the closure of that sector of the A3 motorway. The prompt installation of a GB-InSAR permitted to follow and to understand the temporal evolution of the landslide until the end of the emergency and then safely reopen of the motorway. The main steps of the GB-InSAR interferometry data interpretation used in managing this emergency are described and discussed here. In detail, data collected through a continuous acquisition have permitted the division of the unstable area into three smaller zones characterized by different extents of displacement.
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Tian, Weiming, Zheng Zhao, Cheng Hu, Jingyang Wang, and Tao Zeng. "GB-InSAR-Based DEM Generation Method and Precision Analysis." Remote Sensing 11, no. 9 (April 26, 2019): 997. http://dx.doi.org/10.3390/rs11090997.

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Ground-based interferometric technology plays an important role in the terrain mapping sphere because it is characterized by short observation intervals, a flexible operation environment, and high data precision. Ground-based interferometric synthetic aperture radar (GB-InSAR) has a wide beam, a scene breadth comparative to the slant range, and a large downwards-looking angle. The observation scenes always show the type of slope terrain with various gradients and slope orientations. These particularities cause the invalidation of the typical terrain generation method and produce poor precision analysis results using typical values. This paper first proposes a three-dimensional-coordinate generation method based on the geolocation concept. Then, the models and analyses of the error sources and their propagations are reported. The method of calculating the correlation coefficient is meticulously discussed, and a system error distribution diagram is presented that considers the spatial distribution information of the viewing scene. The result can be adapted to different viewing scenes and encompasses the performance of the whole area, and it will help with baseline optimization. The digital elevation map (DEM) generated by GB-InSAR is compared with one produced by light detection and ranging (LiDAR). The error magnitude and the similarity of the distribution between theory and reality prove the correctness and effectiveness of the presented DEM generation method, the correlation coefficient estimation formula, and the system precision analysis method.
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Dissertations / Theses on the topic "GB-InSAR"

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Zhou, Zhiwei. "The applications of InSAR time series analysis for monitoring long-term surface change in peatlands." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4875/.

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In the past three decades, peatlands all over the world such as upland bogs, tropical fens, have been undergoing significant and rapid degradations. These degradations cause carbon loss and CO2 emissions, and also fuel climate change. In this research, I present three case studies on how space geodetic tools, especially Radar Interferometry (InSAR), can be used to monitor and to advance our understanding of the long-term surface changes in peatlands. First, I investigate the eroding extent and severity of upland UK peatlands using InSAR. Both short wavelength C-band and long wavelength L-band data are explored in this study. I detect a long-term peat subsidence rate of about 0.3 cm/yr, and 2 cm of decrease in peat height between 2002 and 2010. I also examine the coherence performance of C- and L-band over upland bogs. I find L-band data provides better coherence than C-band in upland bogs. Second, I use InSAR time series generated by L-band images to map the spatial and temporal subsidence of drained tropical peatlands in Sumatra, Indonesia. And based on InSAR-derived subsidence rate data, I estimate carbon loss or CO2 emission. Third, I assess the effectiveness of peatland restoration work in in Central Kalimantan, Indonesia using InSAR (L-band images). Restoration effects and impact factors are investigated by the spatial and temporal changes of peat height, which also provide useful information for guiding future restoration activities in this region. Overall, this research suggests that InSAR time series is feasible to monitor long-term peat height change in peatlands, provides new insights into the dynamic surface changes in peatlands, and helps to study the carbon loss and CO2 emissions from peatlands, and understand restoration effects.
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Feng, Wanpeng. "Modelling co- and post-seismic displacements revealed by InSAR, and their implications for fault behaviour." Thesis, University of Glasgow, 2015. http://theses.gla.ac.uk/6284/.

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The ultimate goal of seismology is to estimate the timing, magnitude and potential spatial extent of future seismic events along pre-existing faults. Based on the rate-state friction law, several theoretical physical earthquake models have been proposed towards this goal. Tectonic loading rate and frictional properties of faults are required in these models. Modern geodetic observations, e.g. GPS and InSAR, have provided unprecedented near-field observations following large earthquakes. In theory, according to the frictional rate and state asperity earthquake model, velocity-weakening regions holding seismic motions on faults should be separated with velocity-strengthening regions within which faults slip only aseismically. However, early afterslip following the 2011 MW 9.1 Tohoku-Oki earthquake revealed from GPS measurements was largely overlaid on the historical rupture zones, which challenged the velocity weakening asperity model. Therefore, the performance of the laboratory based friction law in the natural events needs further investigation, and the factors that may affect the estimates of slip models through geodetic modelling should also be discussed systematically. In this thesis, several moderate-strong events were investigated in order to address this important issue. The best-fit co- and post-seismic slip models following the 2009 MW 6.3 Haixi, Qinghai thrust-slip earthquake determined by InSAR deformation time-series suggest that the maximum afterslip is concentrated in the same area as the coseismic slip model, which is similar to the patterns observed in the 2011 Japan earthquake. In this case, complex geometric asperity may play a vital role in the coseismic nucleation and postseismic faulting. The major early afterslip after the 2011 MW 7.1 Van mainshock, which was revealed by one COSMO-SkyMed postseismic interferogram, is found just above the coseismic slip pattern. In this event, a postseismic modelling that did not allow slip across the coseismic asperity was also tested, suggesting that the slip model without slip in the asperities can explain the postseismic observations as well as the afterslip model without constraints on slip in the asperities. In the 2011 MW 9.1 Tohoku-Oki earthquake, a joint inversion with the GRACE coseismic gravity changes and inland coseismic GPS observations was conducted to re-investigate the coseismic slip model of the mainshock. A comparison of slip models from these different datasets suggests that significant variations of slip models can be observed, particularly the locations of the maximum slips. The joint slip model shows that the maximum slip of ~42 m appears near the seafloor surface close to the Japan Trench. Meanwhile, the accumulative afterslip patterns (slip >2 m) determined in previous studies appear in spatial correlation with the Coulomb stress changes generated using the joint slip model. As a strike-slip faulting event, the 2011 MW 6.8 Yushu earthquake was also investigated through co- and post-seismic modelling with more SAR data than was used in previous study. Best slip models suggest that the major afterslip is concentrated in shallow parts of the faults and between the two major coseismic slip patterns, suggesting that the performance of the rate and state frictional asperity model is appropriate in this event. Other postseismic physical mechanisms, pore-elastic rebound and viscoelastic relaxation have also been examined, which cannot significantly affect the estimate of the shallow afterslip model in this study. It is believed that the shallow afterslip predominantly controlled the postseismic behaviour after the mainshock in this case. In comparison to another 21 earthquakes investigated using geodetic data from other studies, complementary spatial extents between co- and post-seismic slip models can be identified. The 2009 MW 6.3 Qinghai earthquake is an exceptional case, in which the faulting behaviours might be dominated by the fault structure (e.g. fault bending). In conclusion, the major contributions from this thesis include: 1) the friction law gives a first order fit in most of natural events examined in this thesis; 2) geometric asperities may play an important role in faulting during earthquake cycles; 3) significant uncertainties in co- and post-seismic slip models can appreciably bias the estimation of fault frictional properties; 4) new insights derived from each earthquake regarding their fault structures and complex faulting behaviours have been observed in this thesis; and (5) a novel package for geodetic earthquake modelling has been developed, which can handle multiple datasets including InSAR, GPS and land/space based gravity changes.
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Liu, Peng. "InSAR observations and modeling of Earth surface displacements in the Yellow River Delta (China)." Thesis, University of Glasgow, 2012. http://theses.gla.ac.uk/3787/.

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Subsidence in river deltas is a complex process that has both natural and human causes (Boesch et al., 1994). The Yellow River delta is used for farming, contains an important nature reserve for wild animals especially for waterfowl, has a population of 1.64 million, and is the location of significant oil fields (Chen et al., 2012). Increasing human activities like farming and petroleum extraction are affecting the Yellow River delta, and one consequence is subsidence. This subsidence may have social, economic and environmental impacts (Syvitski et al., 2009). The purpose of this thesis is to measure the surface displacement in Yellow River delta and to investigate the causes of measured displacement. The use of Interferometric Synthetic Aperture Radar (InSAR) for Earth surface displacement mapping has increased since the 1990s when a lot of radar images become available. InSAR time series techniques identify displacement of an area between different image acquisition times. In this study, StaMPS package was employed to process Envisat ASAR images collected between 2007 and 2010. StaMPS selects only the stable pixels from interferograms to maintain the coherence signals over a long time interval. Consistent results between two descending tracks show subsidence with a mean velocity of up to 30 mm/yr in the radar line of sight direction in Gudao Town (oilfield), Gudong oilfield and Xianhe Town of the delta, and also show that subsidence is not uniform across the delta. Field investigation shows an association between areas of subsidence and of petroleum extraction. In a 9 km2 area of the Gu-Dao Oilfield in the delta, InSAR derived surface deformation is used to model the geometry, volume or pressure change of the deformation source, namely the extraction of fluids, using three different models: the spherical source Mogi type model, the finite prolate spheroid model and the poroelastic disk reservoir model. In general, good fits between InSAR observations and modelled displacements are seen. The source depths estimated in the three models agree well with the published oilfield depth. The subsidence observed in the vicinity of the oilfield is thus suggested to be caused by fluid extraction. For Mogi type model, a uniform subsidence rate of about 7 mm/yr is co-estimated. InSAR observations in Xianhe Town in the delta, which is not affected by oil extraction, also shows 8~12 mm/yr uniform subsidence. It is suggested this uniform subsidence is caused by other sources e.g. loading and sediment compaction. Since InSAR only measures relative displacement, accurate determination of small uniform rate need the reference phase provided by other observations e.g. GPS and levelling. Mogi model provides the volume change in Gudao oilfield. The ellipsoidal source and the disk reservoir model the pressure changes. Additional reservoir information e.g. material parameter will help better confine the model parameters. Although no production data is available for comparison, the volume and pressure changes obtained from the models, together with InSAR observed displacement might be of interest for oil industry, to predict future subsidence in Gudao oilfield.
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BARDI, FEDERICA. "Optimization of ground based radar techniques for early warning systems." Doctoral thesis, 2015. http://hdl.handle.net/2158/1009166.

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The thesis has the main objective of improving landslide risk mitigation strategies, by exploiting advanced technologies, such as Ground Based Interferometric Synthetic Aperture Radar (GB-InSAR) systems. During the research programme, these instruments have been used and optimized to integrate existent Early Warning Systems, in order to reduce landslide risk.
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Book chapters on the topic "GB-InSAR"

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Nolesini, Teresa, William Frodella, Luca Lombardi, Massimiliano Nocentini, Federica Bardi, Emanauele Intrieri, Tommaso Carlà, et al. "Remote 3D Mapping and GB-InSAR Monitoring of the Calatabiano Landslide (Southern Italy)." In Advancing Culture of Living with Landslides, 277–84. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53487-9_31.

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Corsini, Alessandro, Matteo Berti, Antonio Monni, Marco Pizziolo, Francesco Bonacini, Federico Cervi, Giuseppe Ciccarese, et al. "Rapid Assessment of Landslide Activity in Emilia Romagna Using GB-InSAR Short Surveys." In Landslide Science and Practice, 391–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31445-2_51.

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Conference papers on the topic "GB-InSAR"

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Giusti, Elisa, Samuele Gelli, and Marco Martorella. "Atmospheric effects reduction in GB-InSAR applications." In 2021 CIE International Conference on Radar (Radar). IEEE, 2021. http://dx.doi.org/10.1109/radar53847.2021.10027954.

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Zhao, Zheng, Weiming Tian, Yunkai Deng, and Tao Zeng. "GB-InSAR Special Issues during its Applications on DEM Generation." In 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR). IEEE, 2019. http://dx.doi.org/10.1109/apsar46974.2019.9048458.

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Ruiz-Armenteros, Antonio M., José Manuel Delgado-Blasco, Matus Bakon, Francisco Lamas-Fernández, Miguel Marchamalo-Sacristán, Antonio J. Gil-Cruz, Juraj Papco, et al. "Monitoring embankment dams from space using satellite radar interferometry: Case studies from RemoDams project." In 5th Joint International Symposium on Deformation Monitoring. Valencia: Editorial de la Universitat Politècnica de València, 2022. http://dx.doi.org/10.4995/jisdm2022.2022.13883.

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The monitoring procedures with different geotechnical/structural sensors and classical geodetic techniques including GNSS are the usual practices in most of the dams where these controls are established. Other geomatic techniques such as TLS, GB-SAR and multi-temporal InSAR (MT-InSAR), allow the determination of 3D displacements with the advantage of covering a large number of control points. In particular, MT-InSAR techniques enable the detection of displacements at a very low cost compared to other techniques, and without the need for field work or the installation of special equipment. In addition, they can provide a single source of information on the stability of the dam when monitoring programs are not carried out due to lack of funding, resources or other reasons. These techniques provide measurement uncertainties of the order of 1 mm/year, interpreting time series of interferometric phases of coherent reflectors present in the area, called Persistent Scatterers. In this work, we present the adaptation and application of MT-InSAR techniques to monitor embankment dams, obtaining vertical displacements, characterizing their consolidation rates, and allowing the identification of potential problems surrounding the reservoir that require further field investigation. This study is part of the ReMoDams project, a Spanish research initiative developed for monitoring dam structural stability from space using satellite radar interferometry.
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Liu, Miao, Ke-liang Ding, Xianglei Liu, and Zichao Song. "High-speed railway bridge dynamic measurement based on GB-InSAR technology." In International Conference on Intelligent Earth Observing and Applications, edited by Guoqing Zhou and Chuanli Kang. SPIE, 2015. http://dx.doi.org/10.1117/12.2221988.

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Jiang, Zhibiao, Jian Wang, Qian Song, and Zhimin Zhou. "A simplified approach for a downward-looking GB-InSAR to terrain mapping." In 2016 IEEE International Conference on Digital Signal Processing (DSP). IEEE, 2016. http://dx.doi.org/10.1109/icdsp.2016.7868544.

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Huang, Z. S., Y. L. Qi, J. P. Sun, W. X. Tan, Y. P. Wang, and X. L. Yang. "Atmospheric phase correction based on coherent scatterers in GB-SAR interferometry using a single InSAR Pair." In 2016 Progress in Electromagnetic Research Symposium (PIERS). IEEE, 2016. http://dx.doi.org/10.1109/piers.2016.7734879.

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Feng, Huaichao, Pingping Huang, Yaolong Qi, Weixian Tan, Wei Xu, and Xinwei Yan. "A Real-time Selection Method of Adaptive Threshold PS Points for Time Series GB-InSAR Images." In 2021 Photonics & Electromagnetics Research Symposium (PIERS). IEEE, 2021. http://dx.doi.org/10.1109/piers53385.2021.9695131.

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Matas, Gerard, Albert Prades, M. Amparo Núñez-Andrés, Felipe Buill, and Nieves Lantada. "Implementation of a fixed-location time lapse photogrammetric rock slope monitoring system in Castellfollit de la Roca, Spain." In 5th Joint International Symposium on Deformation Monitoring. Valencia: Editorial de la Universitat Politècnica de València, 2022. http://dx.doi.org/10.4995/jisdm2022.2022.13656.

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When monitoring deformations in natural hazards such as rockfalls and landslides, the use of 3D models has become a standard. Several geomatic techniques allow the generation of these models. However, each one has its pros and cons regarding accuracy, cost, sample frequency, etc. In this contribution a fixed-location time lapse camera system for continuous rockfall monitoring using photogrammetry has been developed as an alternative to Light Detection and Ranging (LiDAR) and ground-based interferometric synthetic-aperture radar (GB-InSAR). The usage of stereo photogrammetry allows the obtention of 3D points clouds at a low cost and with a high sample frequency, essential to detect premonitory displacements. In this work the designed system consists of three digital single-lens reflex (DSLR) cameras which collect photographs of the rock slope daily controlled by a Raspberry Pi computer using the open-source library gPhoto2. Photographs are automatically uploaded to a server using 3G network for processing. This system was implemented at Castellfollit de la Roca village (Girona province, Spain), which sits on a basaltic cliff that has shown significant rockfall intensity in recent years. The 3D models obtained will allow monitoring rockfalls frequency, premonitory displacements, and calculate the erosion rate of the slope. All technical decisions taken for the design and implementation on this specific site are discussed and first results shown.
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